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On multistep prediction error methods for time series models
Author(s) -
Stoica Petre,
Nehorai Arye
Publication year - 1989
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.3980080402
Subject(s) - autoregressive–moving average model , series (stratigraphy) , autoregressive model , linear multistep method , computer science , monte carlo method , time series , mean squared prediction error , mathematics , algorithm , econometrics , statistics , machine learning , differential equation , differential algebraic equation , paleontology , biology , ordinary differential equation , mathematical analysis
Multistep prediction error methods for linear time series models are considered from both a theoretical and a practical standpoint. The emphasis is on autoregressive moving‐average (ARMA) models for which a multistep prediction error estimation method (PEM) is developed. The results of a Monte Carlo simulation study aimed at establishing the possible merits of the multistep PEM are presented.